How Real Estate and Web Scraping are Made for Each Other?

Real estate has changed completely with the development of the internet and a lot of other businesses are initially needed heaps of the organization. Technology helps realty dominations like CBRE in scraping and managing their listings internationally.

Automation has dribbled in fields like customer support and email marketing therefore, why not optimize the online property listings to draw a bigger group of buyers?

Most of the realtors are not trained to become technologically intelligent, therefore, manual market research has become more difficult. Web scraping services offers boundless possibilities, which eliminates confusion among the all-encompassing amount of disorganized data.

Web Scraping has Become a Savior

Web scraping makes sure that you have an enormous amount of accurate and reliable real estate information.

Consequently, you can utilize this insight for boosting your company as well as earn considerable rewards.

Extracting real estate data using the Internet with a web scraping service provider gives you the position to provide high-quality real estate solutions and services for the betterment of the customers.

Extracting the web produces metrics, which a realtor can search further to measure sales as well as future customers. These are the parameters, which could be obtained with data scraping:

  • Property’s Type

Accurate Deduction of the Property Values

Want to sell your babyhood home? Don’t mess around with the pricing through shooting in dark as there is ample space for profit after making research as well as observing similar properties as well as their values. Now, the market research can be fast and efficient therefore, you will get the finest deals.

Maximize Rental Yields & Long-Term Sustainability

Before making an investment in the real estate, the most vital thing to keep in mind is rental yields. You would find which properties in the neighborhood are having the finest rental yields by extracting data from the real estate sites. Scraping real estate data shows which real estate types are most general in the given region as well as have the best ROI.

Gathering as well as reviewing data might allow a company to take the best decisions depending on high-quality data. This is also an ideal way of maintaining a strategic lead in the competition.

Tracking Vacancy Rates

Investments in the restricted building could be risky. It is important to look at the property details as well as suburbs having new rental listings to discover what could be the source of better vacancy rates for any particular property.

Having sufficient extracted data, companies could find the difference between diamonds.

Investing Like an Expert

If you wish to constantly invest in the current year, might be you don’t require to listen your elders’ advice from the ’80s. No space is left for imprecise information, which has not got updated ever since the foundation of Google!

Web harvesting permits you to get the latest real estate data, which provides the way to do investment analysis of the listing websites.

Let’s See How to Do it?

Let’s accept that we wish to extract Realtors to get properties with minimum two bedrooms and two baths in Miami as well as compare them to observe which option is better. Just follow these steps in the process.

We’ll begin by using a web scraping tool. You can also do it by creating your individual web scraper, however, it would be time-consuming as well as won’t get a lot of features like a pre-built tool.

We will use our Web Scraping API as it comes with great features including avoiding the IP blocks, geo-targeting, rotating proxies, synchronized requests etc. Also, we will utilize JSDOM and NodeJS.

1. Creating a Web Scraping API Account

This is an easy step. Just register as well as validate your account through email and we’ll go to the following step.

2. API key

You’ll require an API Key to validate your API that you can have from the dashboard.

Just reset the private key anytime with pressing “Reset API Key” option if there is any change of getting it stolen.

3. Application Integration

3.1 Necessary Tools

To make the HTTP request, just install a package as well as jsdom for parsing the HTML resumed from the requests.

3.2 Setting the API Requests Parameters

const params = { api_key: "XXXXXXXXXXXX", url: "" }

3.3 Making the Request

const response = await got('', {searchParams: params}) console.log(response.body)

After making a request, we see that a page is resumed in the HTML format.

3.3 Inspecting the Source Codes

We can search the page as well as elements that we’re involved in using different Developer Tools. To inspect the elements, just right-click on an element and choose ‘Inspect’ option.

We have found that property elements have the class of component_property-card. A few fundamental information about the listings are positioned within this element in the wrapper named property-wrap.

3.5 Parse the HTML

We require to parse request results to manipulate that as the results are returned in the HTML format. JSDOM would complete the job!

const {document} = new JSDOM(response.body).window

3.6 Result Processing

We are looking for the elements having class component_property-card as well as reiterate over them. With each listing, we search corresponding elements with property address, size, price, baths and beds; if these properties are available, we save them in the object. After finishing with current listings, we push that into the array.

Iterating with all listings in an array, we show ones corresponding to the conditions (minimum two beds and two baths).

We wrap this code with the sync function and it needs to look like that:

const {JSDOM} = require("jsdom"); const got = require("got"); (async () => { const params = { api_key: "XXXXXXXXXX", url: "" } const response = await got('', {searchParams: params}) const {document} = new JSDOM(response.body).window const listings = document.querySelectorAll('.component_property-card') const properties = [] listings.forEach(el => { if (el) { const price = el.querySelector('span[data-label="pc-price"]') const beds = el.querySelector('li[data-label="pc-meta-beds"]') const baths = el.querySelector('li[data-label="pc-meta-baths"]') const size = el.querySelector('li[data-label="pc-meta-sqft"]') const address = el.querySelector('div[data-label="pc-address"]') let listing = {} if (price) { listing.price = price.innerHTML } if (beds && beds.querySelector('.meta-value')) { listing.beds = beds.querySelector('.meta-value').innerHTML } if (baths && baths.querySelector('.meta-value')) { listing.baths = baths.querySelector('.meta-value').innerHTML } if (size && size.querySelector('.meta-value')) { listing.size = size.querySelector('.meta-value').innerHTML } if (address && address.textContent) listing.address = address.textContent properties.push(listing) } }) properties.forEach((property) => { if (property.beds >= 2 && property.baths >= 2) { console.log("Address: " + property.address) console.log("Price: " + property.price) console.log("Beds: " + property.beds) console.log("Baths: " + property.baths) console.log("Size: " + property.size + " sqft \n") } }) })();

4. There you are!

Within seconds, you will get all the data on your fingertips! The important thing is how you do it!

Congratulations! You have extracted this web page well.

Use of a Web Scraping Tool is Very Easy

We believe that you’ve understood how website scraping is changing the real estate market.

Those that can adapt to the always-changing technology trends as well as use data will get the best chance of setting an industry pace.

Web scrapers are available in different sizes and shapes. The finest option is try our API before buying anything. Contact X-Byte Enterprise Crawling for real estate data scraping services or ask for a free quote!

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Founder of “X-Byte Enterprise Crawling”, a well-diversified corporation providing Enterprise grade Web Crawling service & solution, leveraging Cloud DaaS model